​Over the last decade, weight bearing CT (WBCT) of the lower extremity has been gaining momentum in evaluation of the foot/ankle and knee - see the figure for the number of WBCT publications across all topics over the years from 2001 to 2021. A growing number of international studies have been investigating the use WBCT in different clinical scenarios, which is promising for improving our understanding of functional anatomy and biomechanics during simulated natural loading of the lower extremity.

However, as with any new technology, there is risk of excessive enthusiasm about the capabilities of WBCT leading to risk of premature application before sufficiently robust scanning protocols are in place. Our recent article focuses on the challenges and caveats concerning the implementation of WBCT, and identifies the work left to obtain robust standardised limb positioning, standardised imaging plane reconstruction, choice of anatomical landmarks and image slices used for radiological measurements, many of which are known to be dependent on such factors. Hence, there is a risk of introducing unintended measurement variation in absence of standardization.

If we ignore the issue of standardisation, the value of introducing WBCT in research and clinical practice will be limited. Measurements of bone and joint geometry in WBCT are often influenced by joint positioning and magnitude of loading, which are factors that need to be considered within a 3-D coordinate system. Some (but not all) WBCT studies examine inter- and intraobserver reproducibility for different radiological measurements at the foot/ankle and knee with reproducibility generally reported to be high. These are often quantified by the intraclass correlation coefficient (ICC), but without adequate information on the specific ICC model used and confidence intervals necessary to correctly interpret ICC values. Often reproducibility is only measured for a specific joint position rather than the more relevant reproducibility of changes between non-WB and WB conditions. Importantly, investigations of test-retest repeatability are also lacking, which is a highly relevant reliability parameter since measurements are often used to study changes over time such as pre- versus postoperative scanning following correctional surgery.
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In the absence of standardised protocols, the current capability of WBCT technology to evaluate factors such as the effects of surgery or structural disease progression is questionable. In our paper we present an overview of the relevant literature on WBCT in the lower extremity with emphasis on factors that may affect measurement reproducibility in the foot/ankle and knee. We also seek to illustrate the downsides of performing WBCT without consensus on imaging procedure and measurement protocols.

​However, rather than just looking at the thickness of cortical bone, the same algorithmic optimisation approach can be used to measure the distance between outer bone surfaces at a joint, hence delivering joint space width. 

But in order to do this, the margins of the joint space need to be defined. Figure 2 summarises how this is achieved at the hip joint, taking the ‘shadow’ of opposing acetabular bone projected back onto the surface of the femoral head and manually segmenting this out for extraction as the ‘joint space patch’. 
 
These steps, along with the joint space measurement algorithm, are performed using the free-to-download software package StradView, developed by Dr Graham Treece and colleagues at the Cambridge University Engineering Department[5]. The joint space patch then acts as a 3-D framework for the joint space mapping algorithm in which the distance between bony surfaces is measured from the imaging data volume and mapped out vertex by vertex (Figure 3).

Figure 3 The algorithm for joint space mapping (JSM) at the hip, with joint space width (JSW) defined as the distance between the acetabular (blue) and femoral (orange) articular bone surfaces in 3-D as measured from the original joint space patch (yellow)[6].

Application of joint space mapping at the hip in collaboration with the Icelandic Heart Association and AGES-Reykjavik cohort showed that embracing a 3-D CT-based approach to joint space width assessment (including 3-D morphological parameters and Kellgren & Lawrence grade derived from the same CT imaging) led to an 18% improvement in prediction of future total hip replacement over the FDA gold standard of 2-D minimum JSW measurement[7]. 
 
In contrast to these hip studies that used supine imaging, an important technical development over the last decade has been the ability to acquire CT imaging at weight bearing lower limb joints with cone beam technology. The orthopaedic foot and ankle community have been early adopters of this, with joint space mapping having now also been demonstrated at the weight bearing ankle[8]. However, it is only relatively recently that weight bearing CT has been gaining popularity at the knee (see the feature by Neil Segal on this page as an exemplar of this pioneering work). 
 
In collaboration with Professor Segal from Kansas, USA, joint space mapping has now also  been applied at the knee (Figure 4) to show its reproducibility, test-retest sensitivity, and relationship with radiographic grading[9]. 

​Figure 4 Joint space mapping at the knee using weight bearing cone beam CT technology in two individuals, one with a Kellgren and Lawrence grade (KLG) of 0 (no osteoarthritis) and another with 4 (severe osteoarthritis).The yellow lines represent the bony articular surfaces within the limits of the joint space perimeter, while the orange lines represent the ‘skeleton’ of the joint at the halfway point, on which the colour wash joint space maps are displayed.

The main perceived advantage of a 3-D joint space mapping approach over radiographic joint space measurement is the potential for greater sensitivity in phenotyping and detecting structural disease progression. However the concurrent and predictive validity of this does now need to be tested in a cohort with relevant clinical outcome measures, as is underway in collaboration with the Multicenter Osteoarthritis Study[10]. 
 
In addition, joint space maps from the same (or different) individuals can be easily compared by registration to a ‘canonical’ surface, which can then not only be used to look at differences between time points and study groups, but also to perform relevant statistical analysis with statistical parametric mapping. This registration process is performed using free-to-download software developed by Dr. Andrew Gee at the Cambridge University Engineering Department[11]. Statistical parametric mapping can be performed using the SurfStat toolbox for MATLAB[12].
 
The robustness and versatility of a 3-D surface-based approach to assessment of structural joint disease has also been translated to magnetic resonance imaging (MRI). Cartilage surface mapping, recently developed and tested by MacKay and colleagues from Cambridge and Norwich, UK, has delivered a platform for multiparametric analysis of MRI data at the knee in prize-winning research recognised by the International Society of Magnetic Resonance Medicine (Figure 5)[13].

Figure 5 Baseline and 6-month follow-up thickness and relaxation time data for a single OA participant displayed on canonical femoral and tibial surfaces (dGEMRIC = delayed gadolinium enhanced MRI of cartilage). Note the spatial heterogeneity of changes and the co-occurrence of both significant positive and negative changes in thickness and T1rho/T2 relaxation times[14].

If you are interested in finding out more or using any of these 3-D imaging analysis techniques, then please contact Dr. Turmezei through his OCTA profile page[15].

Dr. Tom Turmezei
Consultant Radiologist, Norfolk and Norwich University Hospital, UK
Honorary Associate Professor, University of East Anglia, UK
Twitter handles: @3DJointSpace | @tomturmezei

Neil Segal, MD, MS
Dr. George Varghese Professor of Rehabilitation Medicine
Director of Clinical Research
Medical Director of Musculoskeletal Rehabilitation
Department of Rehabilitation Medicine
University of Kansas Medical Center

INTRODUCTION: Meniscal extrusion may be missed on non-weight-bearing MRI. Failure to detect meniscal extrusion has hampered development of effective therapies for osteoarthritis (OA) prevention. Weight-Bearing CT (WBCT) has been found to be more sensitive and accurate for other knee OA features, and more accurate assessment of meniscal damage could potentially improve prediction of worsening joint structure and pain.
 
OBJECTIVE: To assess the rate of detection and severity of meniscal extrusions visualized on WBCT vs. on MRI in older adults with or at elevated risk for knee OA.
 
METHODS: Ancillary to the Multicenter Osteoarthritis Study (MOST), a longitudinal study of knee OA in older Americans, fixed-flexion knee images were acquired using a prototype WBCT scanner. A 3D dataset with an isotropic resolution of 0.37mm was reconstructed from cone beam projections. MRI was acquired using a 1.5T peripheral scanner with participants seated and the knee semi-flexed. Radiologists, blinded to patient identifiers, scored meniscal extrusion severity on each modality (0/1/2/3). Kellgren-Lawrence (KL) grade of knee OA was collected as part of MOST.
 
RESULTS: Of 864 participants with WBCT imaging of the knees, 284 had MRI read for meniscal extrusion. WBCT detected extrusion not detected on MRI in 27.1% of medial and 8.5% of lateral menisci and higher grades of extrusion for 30.6% of medial and 8.8% of lateral menisci (full results in Tables 1 & 2). Knees with greater medial and lateral extrusions visualized on WBCT were predominantly those with early OA (KL<2 for 80.5% and 64% respectively). An example case in which meniscal extrusion visualization differed between modalities is included in Figure 1.

CONCLUSION: WBCT detects meniscal extrusions not detected on standard MRI. Detection of this risk factor for OA progression people with early disease supports a need to assess longitudinal associations between meniscal extrusion detected on WBCT and worsening of pain and joint structure.
 
SPONSOR: NIH-NIAMS R01 AR071648, NIH-NIA U01 AG018832, U01 AG19069
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Peripheral quantitative computed tomography (pQCT) has been used to measure subchondral BMD of the knee. 
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Although pQCT model XCT2000 has a limited gantry diameter, it can still accommodate most individuals with BMI≤ 30 kg/m2. XCT3000 has a larger gantry able to accommodate most knees even for individuals with higher BMI. 
Bennell previously examined subchondral BMD at the 2% and 4% tibial plateau relative to a reference line placed at a level between medial and lateral tibial compartments’ most radio-opaque plateau regions. No femoral condyles were examined, and if compartments were misaligned from the scanner’s Z-axis, the compartment-specific analyses would be oblique.
https://onlinelibrary.wiley.com/doi/pdf/10.1002/art.23795

Subchondral regions of interests marked by periosteal perimeters inset by 20% and total BMD computed to yield subchondral BMD for each compartment. ​

The results of test-retest precision for Protocol 3 applied to healthy and diseased patients, demonstrating sufficient test-retest precision for subchondral BMD measurements overall: ​